JOB SUMMARY This position is dedicated to guiding a highly skilled data science and engineering team to enhance CBRE's sophisticated data curation and data creation processes in support of CBRE Econometric Advisors. The Principle Data Scientist will ensure that thought leaders can easily ingest proprietary and third-party datasets for commercial real estate market research, while also maintaining a production pipeline for a variety of derivative works published in a series of data discovery tools for internal and external client consumption. Successful candidates will be adept at computer science fundamentals, distributed computing, and machine learning.
As Principal Data Scientist at Econometric Advisors, you will guide management of the data structures and pipelines that organize, collect, cleanse and standardize data. You will work closely with data warehouse architects and software developers to empower our thought leaders to perform research and development that generates new products for publication. ESSENTIAL DUTIES AND RESPONSIBILITIES Drive processes for leveraging the firm's enterprise data platform technologies as they evolve and mature.
Lead teams to ensure consistent, accurate, and timely data curation and data creation processes in development, test, and production environments. Lead teams to refine and develop new algorithms that curate and create data from a wealth of structured and unstructured data sources. Partner with data intelligence and the enterprise data platform teams on strategic data initiatives to provide input and help implement data strategy.
Ensure that the current and future datasets are well-documented and in compliance with the firm's overarching data strategy. Drive key reinvestments that will increase the team's capacity to ingest, audit, improve, serve, capture, and push weekly, monthly, and quarterly data sets. Apply advanced leadership skill to bring focused investment of time and resources required to further data engineering at CBRE for discovery by paid and non-paid research clients internal and external worldwide.
Provides formal supervision to direct reports. Recommends staff recruitment, selection, promotion, advancement, corrective action and termination. Conducts performance appraisal and other performance discussions with individual employees.
Plans and monitors appropriate staffing levels and utilization of labor, including overtime. Prepares and delivers performance appraisal for staff. Mentors and coaches team members to further develop competencies.
Leads by example and models behaviors that are consistent with the company's values. QUALIFICATIONS AND EDUCATION: Masters or Ph.D. degree from top tier school in applied data science, computer science, engineering, economics, applied math or related degree.
Minimum 7+ years of experience in statistical analysis, data engineering, and data visualization. Consideration given to equivalent combination of education and experience. Ph.D.
degree from in computer science, economics, engineering, applied math or related degree is highly preferred. Data Scientist Certification or equivalent combination of experience and/or education. REQUIRED KNOWLEDGE AND SKILLS: Ability to comprehend, analyze, and interpret the most complex business documents.
Ability to respond effectively to the most sensitive issues. Ability to write reports, manuals, speeches and articles using distinctive style. Ability to make effective and persuasive presentations on complex topics to employees, clients, top management and/or public groups.
Ability to motivate and negotiate effectively with key employees, top management, and client groups to take desired action. Requires knowledge of financial terms and principles. Ability to calculate intermediate figures such as percentages, discounts, and/or commissions.
Conducts basic financial analysis. Ability to solve advanced problems and deal with a variety of options in complex situations. Requires expert level analytical and quantitative skills with proven experience in developing strategic solutions for a growing matrix-based multi-industry sales environment.
Draws upon the analysis of others and makes recommendations that have a direct impact on the company. Proficiency in methods in analytics and data science algorithms including decision trees, probability networks, association rules, clustering, regression, and neural networks. Knowledge of NLP, text analytics, shell scripting and experience coding in Python/Pandas, R, Java or similar languages.
Knowledge of data modeling, ETL, data processing/warehousing, database architecture, and SQL, SAS, SPSS, and/or STATA. Experience in projects involving cross-functional teams and leaders to build scalable processes and metrics.